The mixed models list is r-sig-mixed-models . nlme:lme is not really designed for crossed random effects. IIRC, it's possible, but not easy. As Kevin said, lme4:lmer is really what you should use.
Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Tue, Jul 20, 2021 at 9:12 AM Kevin Thorpe <kevin.tho...@utoronto.ca> wrote: > You might get better answers on the r-sig-ME list. > > The lmer() function from lme4 handles crossed and non-nested random > effects quite seamlessly. I cannot comment on whether or not lme() can as > well. > > -- > Kevin E. Thorpe > Head of Biostatistics, Applied Health Research Centre (AHRC) > Li Ka Shing Knowledge Institute of St. Michael's > Assistant Professor, Dalla Lana School of Public Health > University of Toronto > email: kevin.tho...@utoronto.ca Tel: 416.864.5776 Fax: 416.864.3016 > > > On Jul 20, 2021, at 10:32 AM, Juan Liu <21707...@zju.edu.cn> wrote: > > > > EXTERNAL EMAIL: > > > > Dear R project, > > > > I am a doctoral student in Zhejiang university in China, I am using lme > function in nlme package and learning the function by Package 'nlme' > document. I am writing this email for some help to build a lme model. > > > > My goal was to include two non-nested random effects in the lme model. > the document described how to write the random effects while I found it > difficult for me to understand. My problem are as below: > > > > > > > > > > In these model, site and year were considered as non nested effects. I > want to set the structure in lme model the same as lmer model(the 1st model > below), and I used the structure "random=list(site=~1,year=~1)"(the 2nd > model below) . According to the result, the lme model was obviously wrong, > for the R2 and AIC were different from that of lmer model. I want to know > to get the same result as lmer model, how should I set the random argument? > > > > Below is the model and results in R, > > > > > > > > > > ################################################################1. lmer > function > > lmer<-lmer(data, y~x1+x2+x3+(1|site)+(1|year)) > > r2(lmer)##58.8%；29.7% > > r.squaredGLMM(lmer)##58.8%; 29.72%;AIC=462.4 > > ###################################################################2. > lme1 > > lme1<-lme(data, y~x1+x2+x3,random = list(site=~1,year=~1)) > > r2(lme1)## NA(can't get the result) > > r.squaredGLMM(lme1)##92.4%; 30.89%;AIC=533 > > > > > > > > > > I will be appreciated for your help. > > > > > > > > > > Yours sincerely, > > > > Juan Liu > > > > Juan Liu > > > > PhD candidate > > > > College of Life Sciences, Zhejiang University > > > > 866 Yuhangtang Road, Hangzhou > > > > Zhejiang 310058, P.R.China > > > > 21707...@zju.edu.cn； liujuan_1...@outlook.com > > > > > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
